Fig. 3: Stamp-seq enables a physical single-cell spatial analysis in non-small cell lung cancer (NSCLC) patients. | Cell Discovery

Fig. 3: Stamp-seq enables a physical single-cell spatial analysis in non-small cell lung cancer (NSCLC) patients.

From: Integrating single-nucleus barcoding with spatial transcriptomics via Stamp-seq to reveal immunotherapy response-enhancing functional modules in NSCLC

Fig. 3

a Schematic representation of the sample collection workflow and sequencing methodology used in this study. b UMAP visualization of the identified cell subsets across all analyzed cells (n = 125,558). c Heatmap displaying the tissue preference of major and minor cell subsets, which was quantified using the Ro/e score. d Spatial map of myeloid and lymphoid cell distribution patterns in representative samples with distinct treatment responses. e Graphical representation of cell communities detected using GraphSAGE. The central cell is defined based on the proportions of neighboring cell types within a 30 μm radius and clustered into five distinct cellular communities, termed “districts”. Cells without neighbors within the 30 μm radius were excluded from the analysis. f Heatmap showing the relative proportions of each cell type across different districts, with row normalization applied. g Spatial distribution of cell types (bottom panel) within each district (top panel) in the T24 pCR sample. h Heatmap depicting the sample preference of each district, quantified by the Ro/e score.

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